Identification of Molecular Subtypes and a Prognostic Signature Based on Inflammation-Related Genes in Colon Adenocarcinoma

Sun

2022

Front. Genet.

Background: The mechanism of DNA damage repair plays an important role in many solid tumors represented by cervical cancer.Purpose: The purpose of this study was to explore the effect of DNA damage repair-related genes on immune function of patients with cervical cancer, and to establish and evaluate a prognosis model based on DNA damage repair-related genes.Methods: In the study, we analyzed the genes related to DNA damage and repair, and obtained two subtypes (F1 and F2). We selected two groups of samples for different selection, and studied which pathways were enriched expression. For different subtypes, the immune score was explored to explain immune infiltration. We got the key genes through screening, and established the prognosis model through the key genes. These 11 key genes were correlated with the expression of common Clusters of Differentiation (CD) genes in order to explore the effects of these genes on immunity.Results: Through the Least absolute shrinkage and selection operator (LASSO) method, we screened 11 genes from 232 candidate genes as the key genes for the prognosis score. Through the Kaplan-Meier method, four genes (HAP1, MCM5, RNASEH2A, CETN2) with significant prognostic significance were screened into the final model, forming a Nomogram with C-index of 0.716 (0.649–1.0).Conclusion: In cervical cancer, DNA damage repair related genes and immune cell infection characteristics have certain association, and DNA damage repair related genes and immune cell infection characteristics can effectively predict the prognosis.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

DNA Damage Repair-Related Genes Signature for Immune Infiltration and Outcome in Cervical Cancer

Sun

2022

Front. Genet.

“…In addition, the patients in the low-risk group had better OS than those in the highrisk group in the training cohort, validation cohort, and entire cohort. The AUC values for 3-year survival in the training cohort and validation cohort were 0.74 and 0.67, respectively, indicating that the model has better predictive ability than similar prognostic models in other studies (AUC = 0.63, AUC = 0.585) (36,37). Then, we identified the risk score as an independent prognostic factor by univariate and multivariate Cox regression analyses.…”

Section: Discussionmentioning

confidence: 80%

An Intratumor Heterogeneity-Related Signature for Predicting Prognosis, Immune Landscape, and Chemotherapy Response in Colon Adenocarcinoma

Liu

et al. 2022

Front. Med.

BackgroundColon adenocarcinoma (COAD) is a frequent malignancy of the digestive system with a poor prognosis and high mortality rate worldwide. Intratumor heterogeneity (ITH) is associated with tumor progression, poor prognosis, immunosuppression, and therapy resistance. However, the relationship between ITH and prognosis, the immune microenvironment, and the chemotherapy response in COAD patients remains unknown, and this knowledge is urgently needed.MethodsWe obtained clinical information and gene expression data for COAD patients from The Cancer Genome Atlas (TCGA) database. The DEPTH2 algorithm was utilized to evaluate the ITH score. X-tile software was used to determine the optimal cutoff value of the ITH score. The COAD patients were divided into high- and low-ITH groups based on the cutoff value. We analyzed prognosis, tumor mutation burden (TMB), gene mutations, and immune checkpoint expression between the high- and low-ITH groups. Differentially expressed genes (DEGs) in the high- and low-ITH groups were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. We performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to screen the prognosis-related genes for the construction of an ITH-related prognostic signature. The nomogram was used to predict the overall survival (OS) of COAD patients. The protein–protein interaction (PPI) network was constructed by using the GeneMANIA database. Principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were employed to explore the differences in biological pathway activation status between the high- and low-risk groups. The proportion and type of tumor-infiltrating immune cells were evaluated by the CIBERSORT and ESTIMATE algorithms. Additionally, we assessed the chemotherapy response and predicted small-molecule drugs for treatment. Finally, the expression of the prognosis-related genes was validated by using the UALCAN database and Human Protein Atlas (HPA) database.ResultsThe OS of the high-ITH group was worse than that of the low-ITH group. A positive correlation between ITH and TMB was identified. In subgroups stratified by age, gender, and tumor stage, the OS of the low-ITH group remained better than that of the high-ITH group. There were dramatic differences in the mutated genes, single nucleotide variant classes, variant types, immune checkpoints and cooccurring and mutually exclusive mutations of the DEGs between the high- and low-ITH groups. Based on the DEGs between the high- and low-ITH groups, we constructed a five-gene signature consisting of CEACAM5, ENO2, GABBR1, MC1R, and SLC44A4. The COAD patients were divided into high- and low-risk groups according to the median risk score. The OS of the high-risk group was worse than that of the low-risk group. The nomogram was used to accurately predict the 1-, 3- and 5-year OS of COAD patients and showed good calibration and moderate discrimination ability. The stromal score, immune score, and ESTIMATE score of the high-risk group were significantly higher than those of the low-risk group, whereas tumor purity showed the opposite trend. The patients classified by the risk score had distinguishable sensitivity to chemotherapeutic drugs. Finally, two public databases confirmed that CEACAM5 and SLC44A4 were upregulated in normal tissues compared with COAD tissues, and ENO2, GABBR1, and MC1R were upregulated in COAD tissues compared with normal tissues.ConclusionOverall, we identified an ITH-related prognostic signature for COAD that was closely related to the tumor microenvironment and chemotherapy response. This signature may help clinicians make more personalized and precise treatment decisions for COAD patients.

“…Moreover, univariate and multivariate Cox regression analyses and ROC curves confirmed that the risk score based on the expression of 13 IFN-γ-related lncRNAs could predict patient prognosis independently of traditional clinical characteristics, which demonstrated the universal applicability of the risk score. The AUC values for 3-year OS in the training cohort and validation cohort were 0.792 and 0.698, respectively, indicating better predictive power compared with other similar prognostic signatures (AUC=0.585, AUC=0.63) ( 25 , 26 ). In addition, the calibration curve showed that the actual observation vs. prediction rates of 1-, 3- and 5-year OS demonstrated a good consensus.…”

Section: Discussionmentioning

confidence: 87%

The Interferon Gamma-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Colon Adenocarcinoma

Liu

et al. 2022

Front. Oncol.

Colon adenocarcinoma (COAD) is one of the most common clinically malignant tumours of the digestive system, with high incidence and mortality and poor prognosis. Interferon-gamma (IFN-γ) and long noncoding RNAs (lncRNAs) have prognostic values and were closely associated with immune microenvironment in COAD. Thus, identifying IFN-γ-related lncRNAs may be valuable in predicting the survival of patients with COAD. In this study, we identified IFN-γ-related lncRNAs and divided COAD patients from the Cancer Genome Atlas (TCGA) database into training and validation sets. Pearson’s correlation analysis and least absolute shrinkage and selection operator (LASSO) Cox regression were performed to select IFN-γ-related lncRNA-associated prognoses. Thirteen lncRNAs (AC025165.8, AC091633.3, FENDRR, LINC00882, LINC01828, LINC01829, MYOSLID, RP11-154H23.4, RP11-20J15.3, RP11-324L17.1, RP11-342A23.2, RP11-805I24.3, SERTAD4-AS1) were identified to construct an IFN-γ-related lncRNA prognostic signature in TCGA training (n =213) and validation (n =213) cohorts. COAD patient risk scores were calculated and classified into high- and low-risk groups based on the median value of the risk scores in each dataset. We compared the overall survival (OS) of patients stratified by age, gender, and stage. The OS in the high-risk group was significantly shorter than that in the low-risk group. In addition, the clinical nomogram incorporating the prognostic signature and clinical features showed a high concordance index of 0.78 and accurately predicted 1-, 3-, and 5-year survival times among COAD patients in the high- and low-risk groups. Based on the risk model, the high- and low-risk groups exhibited distinct differences in the immune system by gene set enrichment analysis (GSEA) functional annotation, and differentially expressed genes (DEGs) between the high- and low-risk groups were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We investigated the expression of multiple immune checkpoint genes in the high- and low-risk groups and plotted Kaplan-Meier survival curves, indicating that immune checkpoint genes, such as LAG3 and PD. L1, STING and TIM 3, were also expressed differently between the two risk groups. Subsequently, there were dramatic differences in mutated genes, SNV (single nucleotide variants) classes, variant types and variant allele frequencies between low- and high-risk patients with COAD. Patients stratified by risk scores had different sensitivities to common chemotherapeutic agents. Finally, we used quantitative real-time polymerase chain reaction (qRT-PCR) assays to demonstrate that three lncRNAs were significantly differentially expressed in COAD tissues and adjacent normal tissues. Considered together, a thirteen-lncRNA prognostic signature has great potential to be a prognostic biomarker and could play an essential role in the immune microenvironment of COAD.